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Taking advantage of a unique measure of corporate culture obtained from advanced machine learning algorithms, this study aims to explore how corporate culture strength is influenced by board independence, which is one of the most crucial aspects of the board of directors. Because of their independence from the corporation, outside independent directors are more likely to be unbiased. As a result, board independence is commonly used as a proxy for board quality.

In addition to the standard regression analysis, the authors execute a variety of additional tests, i.e. propensity score matching, an instrumental variable analysis, Lewbel’s (2012) heteroscedastic identification and Oster’s (2019) testing for coefficient stability.

The results show that stronger board independence, measured by a higher proportion of independent directors, is significantly associated with corporate culture. In particular, a rise in board independence by one standard deviation results in an improvement in corporate culture by 32.8%.

Conducting empirical research on corporate culture is incredibly difficult due to the inherent difficulties in recognizing and assessing corporate culture, resulting in a lack of empirical research on corporate culture in the literature. The authors fill this important void in the literature. Exploiting a novel measure of corporate culture based on textual analysis, to the best of the authors’ knowledge, this study is the first to link corporate culture to corporate governance with a specific focus on board independence.

Exploiting an innovative measure of corporate culture based on machine learning and earnings conference calls, this study aims to investigate how corporate culture is influenced by hostile takeover threats. To sidestep endogeneity, this study uses a unique measure of takeover vulnerability principally based on the staggered implementation of state legislations, which are plausibly exogenous.

In addition to the standard regression analysis, this study also executes a variety of other empirical tests such as propensity score matching, entropy balancing and an instrumental variable analysis, to demonstrate that the results are robust. The final sample includes 27,663 firm-year observations from 4,092 distinct companies from 2001 to 2014.

This study documents that more takeover exposure weakens corporate culture considerably, consistent with the managerial myopia hypothesis. Threatened by the takeover risk, managers tend to behave myopically and are less likely to make long-term investments that promote strong corporate culture in the long run. Additional analysis focusing on a culture of innovation, which is especially vulnerable to managerial myopia, produces similar evidence.

To the best of the authors’ knowledge, this study is the first to explore the effect of takeover susceptibility on corporate culture using a distinctive metric of corporate culture based on textual analysis.

The current national patient safety strategy for the National Health Service (NHS) in England states that actions need to be taken to support the development of a patient safety culture. This includes that local systems should seek to understand staff perceptions of the fairness and effectiveness of serious incident management. This study aims to explore the perspectives of patient safety professionals about what works well and what could be done better to support a patient safety culture at the level of Trust strategy and serious incident governance.

A total of 15 professionals with a role in serious incident management, from five mental health trusts in England, were interviewed using a semi-structured interview guide. Thematic analysis and qualitative description were used to analyse the data.

Participants felt that actions to support a patient safety culture were challenging and required long-term and clinical commitment. Broadening the scope of serious incident investigations was felt to be one way to better understand patient safety culture issues. Organisational influences during the serious incident management process were highlighted, informing approaches to maximise the fairness and objectivity of investigation findings.

The findings of this study offer original insights that the NHS safety system can use to facilitate progression of the patient safety culture agenda. In particular, local mental health trusts could consider the findings in the context of their current strategic objectives related to patient safety culture and operational delivery of serious incident management frameworks.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

This paper investigates the effect of counter-cultural human resources (CCHR) practices on firm performance. Specifically, it investigates the impact of national culture [future orientation (FO), in-group collectivism (I-GC), performance orientation (PO), power distance (PD) and uncertainty avoidance (UA)] on the calculative and collaborative HR practice–firm performance relationship.

This study uses data from the CRANET and GLOBE studies to conduct a multi-level analysis of the impact of national culture on the calculative/collaborative HR–firm performance relationship.

It finds support for both the CCHR and societal-culture fit (SCF) perspectives of national culture, with FO and I-GC supporting the CCHR perspective and the other culture dimensions aligning more closely with SCF.

These findings empirically validate that CCHR practices can help supplement behaviors lacking in the cultural environment in which organizations operate.

This study aims to develop an empathetic and user-centric customer support service design model. Though service design has been a critical research focus for several decades, few studies focus on customer support services. As customer support gains importance as a source of competitive advantage in the present era, this paper aims to contribute to industry and academia by exploring the service design model.

The study adopted a theories-in-use approach to elucidate mental models based on the industry’s best practices. In-depth interviews with 62 professionals led to critical insights into customer service design development, supported by service-dominant logic and theory of mind principles.

The ensuing insights led to a model that connects the antecedents and outcomes of empathetic and user-centric customer service design. The precursors include people, processes and technology, while the results are user experience, service trust and service advocacy. The model also emphasises the significance of the user’s journey and the user service review in the overall service design.

The model developed through this study addresses the critical gap concerning the lack of service design research in customer support services. The key insights from this study contribute to the ongoing research endeavours towards transitioning customer support services from an operational unit to a strategic value-creating function. Future scholars may investigate the applicability of the empathetic user service design across cultures and industries. The new model must be customised using real-time data and analytics across user journey stages.

The empathetic and user-centric design can elevate the customer service function as a significant contributor to the overall customer experience, loyalty and positive word of mouth. Practitioners can adopt the new model to provide superior customer service experiences. This original research was developed through crucial insights from interviews with senior industry professionals.

This research is the original work developed through the key insights from the interview with senior industry professionals.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

The human factor is the most important defense asset against cyberattacks. To ensure that the human factor stays strong, a cybersecurity culture must be established and cultivated in a company to guide the attitudes and behaviors of employees. Many cybersecurity culture frameworks exist; however, their practical application is difficult. This paper aims to demonstrate how an established framework can be applied to determine and improve the cybersecurity culture of a company.

Two surveys were conducted within eight months in the internal IT department of a global software company to analyze the cybersecurity culture and the applied improvement measures. Both surveys comprised the same 23 questions to measure cybersecurity culture according to six dimensions: cybersecurity accountability, cybersecurity commitment, cybersecurity necessity and importance, cybersecurity policy effectiveness, information usage perception and management buy-in.

Results demonstrate that cybersecurity culture maturity can be determined and improved if accurate measures are derived from the results of the survey. The first survey showed potential for improving the dimensions of cybersecurity accountability, cybersecurity commitment and cybersecurity policy effectiveness, while the second survey proved that these dimensions have been improved.

This paper proves that practical application of cybersecurity culture frameworks is possible if they are appropriately tailored to a given organization. In this regard, scientific research and practical application combine to offer real value to researchers and cybersecurity executives.

The purpose of this inductive, exploratory study is to provide foundational insights into the role of management control in dealing with dysfunctional behaviour within accounting schools in changing environment of Australian universities.

Evidence is drawn from semi-structured interviews with 28 current or previous heads of school, research deans, deans of teaching and learning, school managers and human resource managers from 16 Australian universities and interpreted from the theoretical perspective of rational choice theory.

The findings suggest the incidence of a range of dysfunctional behaviours occurring in accounting schools. Even when such behaviours are limited in frequency, their consequences are nevertheless found to have far-ranging and potentially destructive change impacts for both individuals and the university. Formal management control systems designed to address such behaviours are perceived to be largely ineffective in identifying, managing, eliminating or even mitigating the consequences of such dysfunctionality. Instead, it is informal control processes that are preferred in dealing with dysfunctionality.

This study enhances our understanding of the role of management control in dealing with dysfunctional behaviour within university accounting schools, and points not only to the difference between the design and use of management controls but also to the implications of this disconnect between the underlying intent of control design and their actual use in the context of environments that are subject to significant change.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.